In the world of SQL database engines, improving the efficiency of processing SQL queries can be of substantial importance, particularly for large systems processing many thousands of queries a day. For greater clarity, while the term “query” is used throughout this document, it should be understood that this term is also intended to refer to any type of SQL statement, including statements that insert, delete or modify data, based on qualifying criteria. As will be understood by one skilled in the art, such statements are commonly referred to as “SQL statements” or DML (data manipulation language).
Typically most database applications having large tables of data also have corresponding indexes which can be searched in order to locate specific data in the tables. While the database application may search through the index to determine the locations of data in the table satisfying the query and retrieve the indexed data from the table, in certain cases (typically in which the type of data sought has a low distinct cardinality resulting in the retrieval of a significant portion of the table), this approach may be inefficient.
Alternatively, in cases in which a significant portion of the table might have to be retrieved in order to answer a query, the database application may be configured to scan through the entire table to retrieve the data in order to satisfy the query. However, this approach may also prove inefficient, particularly in the event that the table does not contain any data satisfying the query (in which case a negative response is returned).
Accordingly, the applicants have recognized a need for a system and methodology for more efficiently processing certain types of database queries.
The present invention addresses such a need.